CDK1 Promotes Epithelial–Mesenchymal Transition and Migration of Head and Neck Squamous Carcinoma Cells by Repressing ∆Np63α-Mediated Transcriptional Regulation

∆Np63α is a key transcription factor overexpressed in types of squamous cell carcinomas (SCCs), which represses epithelial–mesenchymal transition (EMT) and cell migration. In this study, we found that CDK1 phosphorylates ∆Np63α at the T123 site, impairing its affinity to the target promoters of its downstream genes and its regulation of them in turn. Database analysis revealed that CDK1 is overexpressed in head and neck squamous cell carcinomas (HNSCCs), especially the metastatic HNSCCs, and is negatively correlated with overall survival. We further found that CDK1 promotes the EMT and migration of HNSCC cells by inhibiting ∆Np63α. Altogether, our study identified CDK1 as a novel regulator of ΔNp63α, which can modulate EMT and cell migration in HNSCCs. Our findings will help to elucidate the migration mechanism of HNSCC cells.

Introduction
Head and neck squamous cell carcinomas (HNSCCs) are a group of cancers derived from the mucosal epithelium in the oral cavity, pharynx and larynx. HNSCC is the sixth common cancer worldwide, with about 1 million new cases and a half million deaths per year [1]. Owing to the tendency of regional lymph node metastasis and local recurrence, HNSCC has a low five-year survival rate [2][3][4]. The epithelial-mesenchymal transition (EMT) is a process by which epithelium-derived cancer cells increase their migration ability during the initiation of metastasis [5]. Although it is highly controversial as to whether the EMT is indispensable for cancer metastasis [6][7][8][9], there is mounting evidence of EMT in HNSCCs: by means of multi-omic analyses, EMT or partial EMT, it was found in several subtypes of HNSCC, with alterations of multiple EMT-related molecules including Ecadherin, N-cadherin, vimentin and ITGA6 [10][11][12][13][14][15]. As malignancies arising from epithelia, HNSCC cells generally express high basal levels of epithelial markers such as E-cadherin and K14 [16,17]. TGF-β and EGF, as well as the downstream ERK and AKT pathways, may be involved in activation of the EMT in HNSCCs [1,18,19]. The EMT is documented to endow HNSCC cells with properties of cancer stem cells (CSCs), including the enrichment of the CD44 + /CD24 − population of cancer cells and an increased expression of CSC-related genes [20,21]. ∆Np63α, the major isoform encoded by the p63 gene, is overexpressed in squamous cell carcinomas (SCCs) derived from multiple organs or tissues due to gene amplification [22,23]. The relationship between p63 expression and the prognosis of SCC 2 of 17 patients is controversial: in some cases, a higher p63 level is associated with a worse prognosis [24][25][26][27]; on the contrary, there is also evidence that impaired p63 expression characterizes the biological aggressiveness of high-grade invasive carcinomas [28][29][30]. This discrepancy is likely due to the diversity of p63 isoforms, as well as their opposite roles in different SCC subtypes or in different stages [20]. As a member of the p53 family, ∆Np63α can either activate or inhibit a batch of downstream genes [22,[31][32][33][34]. Recent studies have shown that ∆Np63α inhibits the EMT [22]. Mechanistically, ∆Np63α regulates genes involved in cell adhesion, motility and migration, such as integrins α6, β1 and β4 (ITGA6/B1/B4), and the matrix protein Laminin-γ2, N-cadherin, L1 cell adhesion molecule (L1CAM), bullous pemphigoid antigen 1 (BPAG1), periostin and Wnt-5a [22,[35][36][37]. ∆Np63α is modulated via diverse post-translational modifications, such as phosphorylation, isomerization and ubiquitination, in which a range of enzymes are involved [38].
CDK1 (cyclin-dependent kinase 1) is an important member of the CDK family, which phosphorylates serine/threonine residues of proteins [39][40][41]. In a mixture with A-or B-type cyclins, CDK1 catalyzes the phosphorylation of more than 70 substrates, mainly regulating G1/S phase and G2/M phase transitions in the eukaryotic cell cycle [42][43][44]. In the past decade, a large body of literature has reported that CDK1 is highly expressed in hepatocellular carcinoma, lung cancer, breast cancer, thyroid cancer, colorectal cancer, prostate cancer and other malignant tumors [45][46][47][48][49]. In these scenarios, CDK1 plays key roles in the progression of cancer and survival of cancer cells [40][41][42]. Therefore, CDK1 has become one of the prospective targets for cancer therapy [42,50,51]. According to data from mouse models and patients, inhibition of CDK1 may be an effective strategy to suppress the progression of a range of malignancies [42,45,52]. In addition, recent clinical studies have demonstrated the high level of CDK1 expression in HNSCC patients and its use as a diagnostic biomarker for HNSCCs [50,51]. However, the exact roles and mechanism of this kinase in the development of HNSCCs are unclear.
In this study, we reported that CDK1 mediates the phosphorylation of ∆Np63α at T123. As a consequence, the association of ∆Np63α with its target promoters and ∆Np63αmediated transcriptional regulation is impaired. This regulation of CDK1 on ∆Np63α may lead to EMT and the migration of HNSCC cells, as well as the progression of HNSCC patients. Our findings will help to elucidate the migration mechanism of HNSCCs as well as post-translational modifications (PTMs) of ∆Np63α.

CDK1 Binds to ∆Np63α and Phosphorylates It on Residue T123
To investigate phosphorylation modifications and interacting proteins of ∆Np63α, we conducted an immunoprecipitation (IP) experiment with cell lysate from HEK293T cells exogenously expressing ∆Np63α. With the resultant mass spectrometry (MS) analysis, we identified several ∆Np63α-interacting kinases including CDK1 (listed in Supplementary  Table S1), as well as multiple phosphorylated residues in ∆Np63α (depicted in Supplementary Figure S1). Among these phospho-sites, 15 are located in the DNA binding domain (DBD) or trans-inhibitory domain (TID), both of which are crucial to ∆Np63α-mediated transcriptional regulation [53]. To investigate the effects of these phospho-sites within DBD and TID on ∆Np63α-mediated transcriptional regulation, we generated a series of mutant ∆Np63α constructs, with serine (S) or threonine (T) substituted with alanine (A) to prevent the potential phosphorylation. By means of a luciferase reporter assay using these mutant constructs, with the wild-type ∆Np63α as a control, we found that T123A mutation significantly affects ∆Np63α-mediated transactivation (Supplementary Figure S2). Bioinformatic analysis reveals that the fragment of ∆Np63α containing T123 fits the consensus sequence for CDK1, and this fragment is highly conservative in species ranging from Xenopus to humans (Supplementary Figure S3). Therefore, we focus on the potential CDK1-mediated modification of ∆Np63α.
In this study, the physical interaction between endogenous CDK1 and exogenous ∆Np63α was verified with an independent co-immunoprecipitation (Co-IP) experiment ( Figure 1A). UM1 is a cell line derived from human head and neck squamous cell carcinoma (HNSCC), which expresses a high level of ∆Np63α [54]. To further verify the interaction between the endogenous proteins, we conducted Co-IP experiments with specific antibodies to ∆Np63α and CDK1, respectively. Our results demonstrate that endogenous proteins of ∆Np63α and CDK1 form a stable complex in UM1 cells ( Figure 1B,C). These results suggest that either exogenous or endogenous proteins of ∆Np63α and CDK1 physically interact in cells.
fragment is highly conservative in species ranging from Xenopus to humans (Supplementary Figure S3). Therefore, we focus on the potential CDK1-mediated modification of ∆Np63α.
In this study, the physical interaction between endogenous CDK1 and exogenous ∆Np63α was verified with an independent co-immunoprecipitation (Co-IP) experiment ( Figure 1A). UM1 is a cell line derived from human head and neck squamous cell carcinoma (HNSCC), which expresses a high level of ∆Np63α [54].To further verify the interaction between the endogenous proteins, we conducted Co-IP experiments with specific antibodies to ∆Np63α and CDK1, respectively. Our results demonstrate that endogenous proteins of ∆Np63α and CDK1 form a stable complex in UM1 cells ( Figure  1B,C). These results suggest that either exogenous or endogenous proteins of ∆Np63α and CDK1 physically interact in cells. The cell lysate (input) or IP products were subjected to immunoblot (IB) analysis to detect indicated proteins. (B,C) UM1 cells were lysed and subjected to IP with anti-∆Np63α or anti-CDK1, using homologous IgG as controls. The cell lysate (input) or IP products were subjected to immunoblot (IB) analysis to detect indicated proteins. (D) HEK293 cells transfected with Flag-∆Np63α or its T123A mutant, plus CDK1, were lysed and subjected to IP with anti-Flag or IgG control. The cell lysate (input) or IP products were subjected to IB analysis to detect indicated antigens. P-Thr, phosphorylated threonine. (E) UM1 cells were infected with lentivirus-based shRNA specific to CDK1 (shCDK1#1, using shGFP as a control) and selected with puromycin. The resultant stable cell lines were lysed and subjected to IP with anti-∆Np63α. Then the cell lysate (input) or IP products were subjected to immunoblot (IB) analysis to detect indicated antigens. Furthermore, we co-expressed exogenous wild-type or T123A mutant ∆Np63α with CDK1 in HEK293 cells. The wild-type or mutant ∆Np63α proteins were enriched by means of IP. Then the phosphorylation levels of ∆Np63α in the IP product were detected with the phospho-Thr (P-Thr) antibody ( Figure 1D). Our results show that CDK1 can significantly increase the threonine phosphorylation level of wild-type ∆Np63α but not that of T123A mutant ( Figure 1D). The weak P-Thr bands of T123A mutant suggest other phosphorylated threonine residues in the ∆Np63α protein, which are likely mediated by kinases other than CDK1. This is consistent with our IP-MS analysis, which demonstrates several phosphorylated threonine residues in ∆Np63α (Supplementary Figure S1). To test the modification of endogenous proteins, we knocked down CDK1 with lentivirus-based The cell lysate (input) or IP products were subjected to immunoblot (IB) analysis to detect indicated proteins. (B,C) UM1 cells were lysed and subjected to IP with anti-∆Np63α or anti-CDK1, using homologous IgG as controls. The cell lysate (input) or IP products were subjected to immunoblot (IB) analysis to detect indicated proteins. (D) HEK293 cells transfected with Flag-∆Np63α or its T123A mutant, plus CDK1, were lysed and subjected to IP with anti-Flag or IgG control. The cell lysate (input) or IP products were subjected to IB analysis to detect indicated antigens. P-Thr, phosphorylated threonine. (E) UM1 cells were infected with lentivirus-based shRNA specific to CDK1 (shCDK1#1, using shGFP as a control) and selected with puromycin. The resultant stable cell lines were lysed and subjected to IP with anti-∆Np63α. Then the cell lysate (input) or IP products were subjected to immunoblot (IB) analysis to detect indicated antigens. Furthermore, we co-expressed exogenous wild-type or T123A mutant ∆Np63α with CDK1 in HEK293 cells. The wild-type or mutant ∆Np63α proteins were enriched by means of IP. Then the phosphorylation levels of ∆Np63α in the IP product were detected with the phospho-Thr (P-Thr) antibody ( Figure 1D). Our results show that CDK1 can significantly increase the threonine phosphorylation level of wild-type ∆Np63α but not that of T123A mutant ( Figure 1D). The weak P-Thr bands of T123A mutant suggest other phosphorylated threonine residues in the ∆Np63α protein, which are likely mediated by kinases other than CDK1. This is consistent with our IP-MS analysis, which demonstrates several phosphorylated threonine residues in ∆Np63α (Supplementary Figure S1). To test the modification of endogenous proteins, we knocked down CDK1 with lentivirusbased shRNA in UM1 cells, with which we conducted IP and IB analysis. The results demonstrate that CDK1 knockdown leads to a lower phosphorylation level of threonine (P-Thr) in ∆Np63α ( Figure 1E). These data suggest that CDK1 phosphorylates ∆Np63α at T123 in cells.

CDK1 Impairs Association of ∆Np63α with Its Downstream Gene Promoters to Inhibit ∆Np63α-Mediated Transcriptional Regulation
Next, we investigated whether CDK1 affects the transcriptional activity of ∆Np63α using luciferase reporters, respectively, driven by promoters of K14 and BPAG1, both of which are downstream target genes of ∆Np63α [22]. The luciferase reporter assays reveal that overexpression of CDK1 impairs ∆Np63α-mediated luciferase expression driven by K14 or BPAG1 promoter (K14-Luc or BPAG1-Luc, Figure 2A,B). Our further data demonstrate that CDK1 suppresses ∆Np63α-mediated K14-Luc expression in a dose-dependent manner ( Figure 2C). To investigate the effects of endogenous CDK1 on the transactivity of ∆Np63α, we knocked down CDK1 and performed luciferase reporter assays. The results reveal that knockdown of CDK1 induces a significant augmentation of the ∆Np63α-mediated expression of either K14-Luc or BPAG1-Luc ( Figure 2D,E). On the other hand, we treated the cells with RO3306, which is a specific CDK1 inhibitor [45]. The results reveal that RO3306 enhances ∆Np63α-mediated K14-Luc expression in a dose-dependent manner ( Figure 2F). These data suggest that CDK1 inhibits ∆Np63α-mediated transcriptional regulation.
shRNA in UM1 cells, with which we conducted IP and IB analysis. The results demonstrate that CDK1 knockdown leads to a lower phosphorylation level of threonine (P-Thr) in ∆Np63α ( Figure 1E). These data suggest that CDK1 phosphorylates ∆Np63α at T123 in cells.

CDK1 Impairs Association of ∆Np63α with Its Downstream Gene Promoters to Inhibit ∆Np63α-Mediated Transcriptional Regulation
Next, we investigated whether CDK1 affects the transcriptional activity of ∆Np63α using luciferase reporters, respectively, driven by promoters of K14 and BPAG1, both of which are downstream target genes of ∆Np63α [22]. The luciferase reporter assays reveal that overexpression of CDK1 impairs ∆Np63α-mediated luciferase expression driven by K14 or BPAG1 promoter (K14-Luc or BPAG1-Luc, Figure 2A,B). Our further data demonstrate that CDK1 suppresses ∆Np63α-mediated K14-Luc expression in a dosedependent manner ( Figure 2C). To investigate the effects of endogenous CDK1 on the transactivity of ∆Np63α, we knocked down CDK1 and performed luciferase reporter assays. The results reveal that knockdown of CDK1 induces a significant augmentation of the ∆Np63α-mediated expression of either K14-Luc or BPAG1-Luc ( Figure 2D,E). On the other hand, we treated the cells with RO3306, which is a specific CDK1 inhibitor [45]. The results reveal that RO3306 enhances ∆Np63α-mediated K14-Luc expression in a dosedependent manner ( Figure 2F). These data suggest that CDK1 inhibits ∆Np63α-mediated transcriptional regulation.  of K14-or BPAG1-Luc and TK-Renilla, plus Flag-∆Np63α and Myc-CDK1, shCDK1#1, increasing dose of Myc-CDK1 or RO3306 (a specific CDK1 inhibitor), as indicated. Firefly and Renilla luciferase activities were measured, while IB analyses were performed to detect indicated proteins in parallel. The K14-or BPAG1-Luc expression levels were normalized to Renilla activity and presented as means ± SD (n = 3). Two-tailed t-test was used for comparison between two groups; ***, p < 0.001; **, p < 0.01; *, p < 0.05. (G) Chromatin immunoprecipitation (ChIP) assays were performed with UM1 cells stably overexpressing Flag-∆Np63α or Flag-∆Np63α plus CDK1, using anti-Flag. DNA samples precipitated with either anti-Flag or mock IgG, as well as equivalent input, were subjected to quantitative polymerase chain amplification (qPCR) to detect fragments of BPAG1 and N-cadherin promoters. ∆Np63α-associated promoter fragments were assessed and normalized with input and mock IgG groups (means ± SD; n = 3; *, p < 0.05).
As mentioned above, T123, the residue phosphorylated by CDK1, resides in the DNA binding domain (DBD) of ∆Np63α (Supplementary Figure S1). To investigate whether CDK1 affects the association between ∆Np63α and the promoters of its downstream genes, we performed an experiment of chromatin immunoprecipitation followed by quantitative polymerase chain reaction (ChIP-qPCR) with cells overexpressing Flag-tagged ∆Np63α in combination with or without CDK1. The fragments of BPAG1 and N-Cadherin promoters were previously reported as direct targets of ∆Np63α [55], which was confirmed in our experiments (Supplementary Figure S4). Our ChIP-qPCR results demonstrate that promoter fragments of BPAG1 and N-Cadherin are detected in the ChIP products, while the simultaneous expression of exogenous CDK1 decreases the precipitated fragments of BPAG1 and N-Cadherin promoters ( Figure 2G). Together, these results suggest that CDK1 reduces the affinity between ∆Np63α and promoters of its downstream genes and, consequently, inhibits ∆Np63α-mediated transcriptional regulation.

T123A Mutation in ∆Np63α
Abrogates the Inhibitory Effect of CDK1 on ∆Np63α-Mediated Transcriptional Regulation Our aforesaid data indicate that T123 is a residue relevant to ∆Np63α activity (Supplementary Figure S2), which is negatively regulated by CDK1 ( Figure 2). To further confirm this hypothesis, we performed luciferase reporter assays with T123A mutant ∆Np63α, comparing its transactivity to that of wild-type ∆Np63α as well as the effects of CDK1 on them. Our data demonstrate that T123A mutant ∆Np63α has a higher transactivity than the wild type has ( Figure 3A-D). This is consistent with our data shown in Supplementary Figure S2. On the other hand, both the overexpression and knockdown of CDK1 fail to affect the luciferase expression mediated by T123A mutant (Figure 3A-D). These data indicate that CDK1 inhibits the transactivity of ∆Np63α by phosphorylating this transcription factor at T123.

CDK1 Is Upregulated in Head and Neck Squamous Cell Carcinomas (HNSCCs) and Is Correlated to Malignant Progression of HNSCCs
∆Np63α plays key roles in cell migration and metastasis of head and neck squamous cell carcinomas (HNSCCs) [22]. To explore the correlation between HNSCC and the expression of CDK1, bioinformatics analysis was performed using the Kaplan-Meier plotter database. The result demonstrated that CDK1 expression is significantly higher in HNSCCs than in normal tissues; in metastatic HNSCCs, CDK1 is further upregulated ( Figure 4A). The survival analysis shows that HNSCC patients with a high expression of CDK1 have lower survival rates than those with low CDK1 expression ( Figure 4B). These data indicate that CDK1 plays key roles in tumorigenesis and the progression of HNSCCs, especially in metastasis of HNSCCs.

CDK1 Promotes Epithelial-Mesenchymal Transition (EMT) and Migration of HNSCC Cells
To investigate the roles of CDK1 in HNSCC cell migration, we generated stable cell lines overexpressing exogenous CDK1 and performed transwell assays. As shown in Figure 5A, the Flag-tagged CDK1 was exogenously expressed in UM1 and Cal27 cells, both of which are derived from HNSCCs. The results of the transwell assay show that cells stably overexpressing CDK1 possess a higher migration ability, compared with the control cells ( Figure 5B,C). Our RT-qPCR results reveal that EMT markers, N-cadherin and vimentin [56], are significantly upregulated in CDK1-overexpressing cells ( Figure 5D). On the other hand, we knocked down endogenous CDK1 in UM1 and Cal27 cells ( Figure 5E) and performed transwell assays ( Figure 5F,G). The results reveal that the depletion of CDK1 induces a significant decrease in the migration of these cells. The RT-qPCR analyses demonstrate the significant downregulation of EMT markers, N-Cadherin and vimentin, in CDK1-knockdown cells ( Figure 5H). Together, these data suggest that CDK1 promotes EMT and cell migration in HNSCC cells.  . Two-tailed t-test was used for comparison between two groups; ***, p < 0.001; **, p < 0.01; *, p < 0.05; ns, nonsignificant.

CDK1 Is Upregulated in Head and Neck Squamous Cell Carcinomas (HNSCCs) and is Correlated to Malignant Progression of HNSCCs
∆Np63α plays key roles in cell migration and metastasis of head and neck squamous cell carcinomas (HNSCCs) [22]. To explore the correlation between HNSCC and the expression of CDK1, bioinformatics analysis was performed using the Kaplan-Meier plotter database. The result demonstrated that CDK1 expression is significantly higher in HNSCCs than in normal tissues; in metastatic HNSCCs, CDK1 is further upregulated ( Figure 4A). The survival analysis shows that HNSCC patients with a high expression of CDK1 have lower survival rates than those with low CDK1 expression ( Figure 4B). These data indicate that CDK1 plays key roles in tumorigenesis and the progression of HNSCCs, especially in metastasis of HNSCCs.

CDK1 Promotes Epithelial-Mesenchymal Transition (EMT) and Migration of HNSCC Cells
To investigate the roles of CDK1 in HNSCC cell migration, we generated stable cell lines overexpressing exogenous CDK1 and performed transwell assays. As shown in Figure 5A, the Flag-tagged CDK1 was exogenously expressed in UM1 and Cal27 cells, both of which are derived from HNSCCs. The results of the transwell assay show that cells stably overexpressing CDK1 possess a higher migration ability, compared with the control cells ( Figure 5B,C). Our RT-qPCR results reveal that EMT markers, N-cadherin and vimentin [56], are significantly upregulated in CDK1-overexpressing cells ( Figure  5D). On the other hand, we knocked down endogenous CDK1 in UM1 and Cal27 cells ( Figure 5E) and performed transwell assays ( Figure 5F,G). The results reveal that the depletion of CDK1 induces a significant decrease in the migration of these cells. The RT-qPCR analyses demonstrate the significant downregulation of EMT markers, N-Cadherin and vimentin, in CDK1-knockdown cells ( Figure 5H). Together, these data suggest that CDK1 promotes EMT and cell migration in HNSCC cells.  The qPCR data were presented as means ± SD (n = 3). ***, p < 0.001; **, p < 0.01; *, p < 0.05.

CDK1 Impairs Inhibitions of HNSCC Cell EMT and Migration Induced by Wild-Type ∆Np63α But Not Those by Its T123A Mutant
As mentioned above, ∆Np63α can inhibit EMT and migration in HNSCC cells [22]. To investigate whether CDK1 can modulate ∆Np63α-induced inhibition of EMT and cell migration via phosphorylating ∆Np63α at T123, we overexpressed ∆Np63α or its T123A mutant with or without CDK1 in UM1 cells ( Figure 6A), with which we conducted transwell assays and RT-qPCR ( Figure 6B-D). The results of transwell assays reveal that overexpression of ∆Np63α induces a significant inhibition of cell migration, while the The qPCR data were presented as means ± SD (n = 3). ***, p < 0.001; **, p < 0.01; *, p < 0.05.

CDK1 Impairs Inhibitions of HNSCC Cell EMT and Migration Induced by Wild-Type ∆Np63α but Not Those by Its T123A Mutant
As mentioned above, ∆Np63α can inhibit EMT and migration in HNSCC cells [22]. To investigate whether CDK1 can modulate ∆Np63α-induced inhibition of EMT and cell migration via phosphorylating ∆Np63α at T123, we overexpressed ∆Np63α or its T123A mutant with or without CDK1 in UM1 cells ( Figure 6A), with which we conducted transwell assays and RT-qPCR ( Figure 6B-D). The results of transwell assays reveal that overexpression of ∆Np63α induces a significant inhibition of cell migration, while the T123A mutation further exacerbates the migration inhibition; CDK1 significantly impairs cell migration inhibition induced by ∆Np63α, but not that by its T123A mutant ( Figure 6B,C). The RT-qPCR analyses demonstrate that mesenchymal markers, N-cadherin and vimentin [56], are significantly downregulated in UM1 cells overexpressing ∆Np63α, and are restored by the simultaneous overexpression of CDK1 ( Figure 6D). In parallel, ∆Np63α significantly induces the expression of BPAG1 and ITGA6, which are markers of epithelial characteristics and inhibit cell migration [57,58]; the simultaneous overexpression of CDK1 can significantly impair the ∆Np63α-induced upregulation of BPAG1 and ITGA6 ( Figure 6D). These results suggest that CDK1 impairs the EMT and migration inhibitions induced by ∆Np63α by phosphorylating its T123 residue.

Knockdown of ∆Np63α Significantly Rescues Migration Inhibition Induced by CDK1 Depletion in HNSCC Cells
To confirm the involvement of ∆Np63α in the CDK1-modulated migration of HNSCC cells, we knocked down endogenous CDK1 and (or) ∆Np63α in UM1 cells ( Figure  7A). By means of transwell assays using these stable cell lines, we found that the depletion were constructed with lentiviral infection and identified by means of IB analysis. (B) UM1 cells overexpressing CDK1 and (or) ∆Np63α were subjected to transwell assay. Representative crystal violet staining images of migrated cells on the underside were shown. (C) Quantification of effects of CDK1 and (or) ∆Np63α overexpression or ablation on migration ability based on transwell assays (means ± SD, n = 3). One-way ANOVA test was used for comparison between two groups. ***, p < 0.001; **, p < 0.01. (D) The abovementioned cell lines were subjected to RT-qPCR analysis to measure mRNA levels of N-cadherin, vimentin, BPAG and ITGA6 (normalized with GAPDH). The qPCR data are presented as means ± SD (n = 3). ***, p < 0.001; **, p < 0.01; *, p < 0.05.

Knockdown of ∆Np63α Significantly Rescues Migration Inhibition Induced by CDK1 Depletion in HNSCC Cells
To confirm the involvement of ∆Np63α in the CDK1-modulated migration of HNSCC cells, we knocked down endogenous CDK1 and (or) ∆Np63α in UM1 cells ( Figure 7A). By means of transwell assays using these stable cell lines, we found that the depletion of ∆Np63α induces the enhanced migration of UM1 cells and significantly rescues migration inhibition induced by knockdown of CDK1 ( Figure 7B,C). On the other hand, the ablation of CDK1 can still attenuate cell migration even in the scenario where ∆Np63α is depleted to an undetectable level (Figure 7). This indicates that CDK1 promotes cell migration, at least in part, via impairing the inhibitory effect of ∆Np63α on the migration ability of HNSCC cells.

Discussion
Exploring the cell migration mechanism of cancer cells is of great significance for cancer treatment, especially for head and neck squamous cell carcinomas (HNSCCs), which tends to metastasize to proximal lymph nodes [59,60]. ∆Np63α is the predominant isoform encoded by p63 gene, and plays key roles in the tumorigenesis of a variety of

Discussion
Exploring the cell migration mechanism of cancer cells is of great significance for cancer treatment, especially for head and neck squamous cell carcinomas (HNSCCs), which tends to metastasize to proximal lymph nodes [59,60]. ∆Np63α is the predominant isoform encoded by p63 gene, and plays key roles in the tumorigenesis of a variety of squamous cell carcinomas (SCCs) [61,62]. Generally, ∆Np63α is upregulated in SCCs due to gene amplification. It can promote neoplasia of SCCs by facilitating cell proliferation, while it inhibits cancer invasion and metastasis at late stages of SCCs [22]. Mechanistically, it can inhibit epithelial-mesenchymal transition (EMT) and cell migration by regulating the expression of various genes related to cell adhesion and motility [35,37]. Previous data from our lab and other groups reveal that p63 proteins can be phosphorylated and modulated by several kinases [53,[63][64][65][66][67][68].
According to our IP-MS analysis, we identified the T123 in ∆Np63α is one of the phospho-sites affecting transactivity ( Supplementary Figures S1 and S2). On the other hand, CDK1 is one of the candidate ∆Np63α-interacting proteins (Supplementary Table S1), whose consensus binding sequence fits the fragment containing T123 (Supplementary Figure S3). According to our data, there are several phospho-sites affecting the transactivity of ∆Np63α in addition to T123, though the T123A mutation leads to the biggest rise in ∆Np63α transactivity (Supplementary Figure S2). It remains to be investigated which kinases mediate the phosphorylation of these residues in our system. In this study, we confirmed that CDK1 directly binds to ∆Np63α and phosphorylates it at T123 (Figure 1). Our data demonstrate that CDK1 significantly inhibits ∆Np63α-mediated transcriptional regulation (Figure 2A-F). According to our result of the chromatin immunoprecipitation (ChIP) assay, CDK1 impairs the association between ∆Np63α and the promoters of its downstream genes, including the targets of both transactivation (BPAG1) and transinhibition (N-Cadherin) ( Figure 2G). On the other hand, the T123A mutation in ∆Np63α, which eliminates phosphorylation mediated by CDK1 ( Figure 1D,E), abrogates the inhibitory effect of CDK1 on ∆Np63α-mediated transcriptional regulation ( Figure 3). These data suggest that the CDK1-mediated phosphorylation of ∆Np63α at T123 impairs the affinity between this transcription factor and its target promoters, resulting in weakened regulation of ∆Np63α on its downstream genes.
CDK1 is a cell cycle-related kinase, which can promote the cell cycle via phosphorylating key substrates including Rb and transactivating genes that are regulated by E2F [44]. Due to its pivotal roles in cell proliferation, diverse CDK1 inhibitors have been explored, such as flavopiridol, dinaciclib, AZD5438, AT-7519 and RO3306. In clinical or preclinical trials, these inhibitors demonstrate significant inhibition on malignancies including chronic lymphocytic leukemia, mantle cell lymphoma, hepatocellular carcinoma and gastrointestinal stromal tumor [42,45,52]. On the other hand, these CDK inhibitors may cause some adverse effects, e.g., the likelihood of recurrence induced by senescent cells in palbociclib treatment [69,70]. It remains to be seen how to avoid the side effects and whether they may apply to other cancer types [42]. In our study, we did observe the pro-proliferative effect of CDK1 on HNSCC cells, which is independent of ∆Np63α (data not shown). In this paper, we reported that CDK1 promotes the migration of HNSCC cells by modulating ∆Np63α: the overexpression of CDK1 enhances cell migration ( Figure 5B,C) and significantly impairs the migration inhibition induced by the overexpression of wild-type ∆Np63α, but not that by its T123A mutant ( Figure 6B,C); knockdown of CDK1 induces an inhibition of cell migration ( Figure 5F,G), which can be partially rescued by the simultaneous ablation of ∆Np63α (Figure 7). It has been previously reported that CDK1 promotes the migration and metastasis of cancer cells, e.g., colorectal carcinoma and breast cancer cells, by phosphorylating proteins such as EZH2 and activating pathways such as the Wnt/β-Catenin and ERK/GSK3β/SNAI axes [71][72][73]. In our study, we observed that the depletion of ∆Np63α fails to completely rescue the migration inhibition induced by CDK1 knockdown (Figure 7). This indicates that CDK1 may also promote HNSCC cell migration in ∆Np63α-independent pathways (Figure 7). Recent studies suggest that the basal subtypes of HNSCCs undergo the EMT process (at least partial EMT) during metastasis, while mesenchymal, classical and atypical subtypes metastasize independently of the EMT [13,15]. Our in vitro investigation indicates that CDK1 modulates the ∆Np63α-mediated inhibition of EMT in basal HNSCC cells, UM1 and Cal27: CDK1 overexpression upregulates ( Figure 5D), while the ablation of CDK1 downregulates ( Figure 5H), mesenchymal markers N-Cadherin and vimentin; ∆Np63α-induced downregulation of mesenchymal markers (N-Cadherin and vimentin), as well as upregulation of epithelial markers (BPAG1 and ITGA6), are impaired by CDK1 ( Figure 6D). Our results are consistent with data from other groups, which reveal that CDK1 promotes the migration of lung cancer cells and colorectal cancer cells via different mechanisms [72,74]. Our data show that CDK1 may, at least in part, promote the EMT and migration of HNSCC cells by phosphorylating ∆Np63α and inhibiting ∆Np63α-mediated transcriptional regulation.
The results of the database analysis reveal that the expression of CDK1 is upregulated in HNSCCs, especially in metastatic ones ( Figure 4A). On the other hand, a high level of CDK1 correlates with a shorter survival of HNSCC patients ( Figure 4B). In combination with the fact that ∆Np63α is a key transcription factor controlling cancer cell migration and metastasis in multiple SCC cancer types [22], our data indicate that CDK1 may facilitate metastasis of HNSCCs, by phosphorylating and inhibiting ∆Np63α. Despite a lack of direct in vivo evidence, our findings shed new light on the mechanisms of the EMT and migration of HNSCC cells. Given the differences between cultured cells and actual tumors, this CDK1-mediated regulation of ∆Np63α, as well as its effects on EMT and cell migration, will be further verified in mouse models in our future work. It is also worthwhile to test whether CDK1 inhibitors can effectively intervene in the progression of HNSCCs in animals and patients.

Bioinformatics Analyses
The mRNA level of CDK1 in tumor versus normal tissues and the survival analysis of CDK1 in HNSCCs were determined on website http://www.kmplot.com (accessed on 18 February 2021).

Reverse Transcription Quantitative PCR (RT-qPCR) Analysis
Total RNA was isolated by TransZol (Transgen Biotech), followed by reverse transcription using Hifair II 1st strand cDNA Synthesis SuperMix for qPCR (Yeasen). Quantitative PCR analysis was performed in a CFX96 Real-Time PCR System (Bio-Rad) using the SYBR Green qPCR Master Mix (MCE) according to the manufacturer's instructions. The primer sequences were as follows: GAPDH, 5 -GACAAGAACTCCACTTCCTG-3 and 5 -GGCAGAGATGATGACCCTT TT-3 ;

Immunoprecipitation (IP)
For the co-immunoprecipitation (Co-IP) experiment, HEK293T cells were co-transfected to express Myc-tagged CDK1 or (and) Flag-tagged ∆Np63α. Cells were lysed using cell lysis buffer for Western and IP (Beyotime) with protease and phosphatase inhibitor cocktail for general use (Beyotime) on ice for 10 min. Lysates were cleared by centrifugation at 13,000 rpm for 15 min. Protein concentration was determined using the Bradford protein assay reagent (Coolaber). Then, 2 mg of total proteins from cell lysates were incubated with anti-Flag or normal mouse IgG as control at 4 • C for 8 h, and the immune complexes were precipitated with protein A + G-agarose at 4 • C for 2 h. The immunoprecipitates were washed with lysis buffer, separated by SDS-PAGE and subjected to IB as described previously [79,80,82].

Transwell Migration Assay
Corning Transwell plates (Transparent PET Membrane, 24-well 8.0 µm pore size, Corning, NY, USA) without Matrigel were used to detect the longitudinal migration ability of cells. A total of 0.5 × 10 5 cells suspended in 200 µL of culture medium with 0.1% FBS were seeded in the upper chamber, and 500 µL of medium with 10% FBS was placed in the lower chamber. After an incubation at 37 • C in a humidified 5% CO 2 incubator for 24 h (the doubling time of UM1 and Cal27 is about 48 h), a cotton swab was used to remove the cells adhering to the membrane of the upper chamber. The migrated cells on the lower side of the filter membrane surface were stained with 0.1% crystal violet, and the fields of cells were captured by Nikon eclipse Ti-U, Japan. Five fields were randomly chosen for each well to count migrated cells to assess the migration ability as described previously [54].

Luciferase Reporter Assay
Luciferase assays were performed as described previously [53,84]. HEK293T cells were transfected with a mixture of K14-or BPAG1-Luc and pRL-TK-Renilla plus indicated plasmids or siRNAs. Total amount of DNAs or RNAs was balanced with control vectors or scramble control RNAs. Cells were harvested at 48 h post transfection and lysed in Passive Lysis Buffer (Beyotime). Lysates were analyzed for firefly and Renilla luciferase activities using the Dual Luciferase Reagent Assay Kit (Beyotime). Luminescence was measured in a luminometer. Relative luciferase activity was determined by normalizing luciferase activity with Renilla.

Statistical Analysis
Statistical analyses were conducted using GraphPad Prism 8 software. Data are presented as means ± SD from at least three independent experiments performed in triplicate; Two-tailed t-test or one-way ANOVA test is employed to assess the significance (***, p < 0.001; **, p < 0.01; *, p < 0.05). The present data are from three independent experiments performed in triplicate.


MicroRNAs, Tristetraprolin Family Members and HuR: A Complex Interplay Controlling Cancer-Related Processes

Simple Summary AU-rich Element Binding Proteins (AUBPs) represent important post-transcriptional regulators of gene expression by regulating mRNA decay and/or translation. Importantly, AUBPs can interfere with microRNA-dependent regulation by (i) competing with the same binding sites on mRNA targets, (ii) sequestering miRNAs, thereby preventing their binding to their specific targets or (iii) promoting miRNA-dependent regulation. These data highlight a new paradigm where both miRNA and RNA binding proteins form a complex regulatory network involved in physiological and pathological processes. However, this interplay is still poorly considered, and our current models do not integrate this level of complexity, thus potentially giving misleading interpretations regarding the role of these regulators in human cancers. This review summarizes the current knowledge regarding the crosstalks existing between HuR, tristetraprolin family members and microRNA-dependent regulation. Abstract MicroRNAs represent the most characterized post-transcriptional regulators of gene expression. Their altered expression importantly contributes to the development of a wide range of metabolic and inflammatory diseases but also cancers. Accordingly, a myriad of studies has suggested novel therapeutic approaches aiming at inhibiting or restoring the expression of miRNAs in human diseases. However, the influence of other trans-acting factors, such as long-noncoding RNAs or RNA-Binding-Proteins, which compete, interfere, or cooperate with miRNAs-dependent functions, indicate that this regulatory mechanism is much more complex than initially thought, thus questioning the current models considering individuals regulators. In this review, we discuss the interplay existing between miRNAs and the AU-Rich Element Binding Proteins (AUBPs), HuR and tristetraprolin family members (TTP, BRF1 and BRF2), which importantly control the fate of mRNA and whose alterations have also been associated with the development of a wide range of chronic disorders and cancers. Deciphering the interplay between these proteins and miRNAs represents an important challenge to fully characterize the post-transcriptional regulation of pro-tumorigenic processes and design new and efficient therapeutic approaches.

Introduction
Trans-acting factors controlling the fate of mRNA importantly contribute to gene expression regulation. Among them, intense efforts have been devoted to non-coding RNAs, mostly miRNAs, which mainly bind to the 3 Untranslated Region (3 -UTR) of target mR-NAs and promote either mRNA degradation and/or translation inhibition [1]. The importance of miRNAs in physiological and pathological processes is now well-established. For most human diseases, the altered miRnome has been identified through high-throughput approaches and has suggested appealing therapeutic approaches to target deregulated miRNAs [2,3]. However, increasing studies indicate that the post-transcriptional regulation of gene expression is more complex than originally thought and requires other regulators, such as long-non-coding RNAs (lncRNA) or RNA-Binding Proteins (RBPs) [4][5][6]. AU-Rich Element Binding Proteins (AUBPs) are RBPs of particular importance due to their ability to bind to AU-rich sequences in the 3 UTR of immediate response genes (e.g., TNF-α, cyclooxygenase-2) and promote either their decay or translation inhibition [7,8]. Similarly, for miRNAs, deregulated expression/activity of AUBPs strongly contributes to the development of a wide range of diseases due to their ability to control a whole set of genes associated with pathological processes, including inflammation (e.g., Tumor Necrosis Factor alpha, TNFα), fibrosis, metabolism, or carcinogenesis [9]. These proteins can interfere, compete, or synergize with miRNA-dependent regulation [10,11] and conversely, miRNAs can also regulate the expression of AUBPs. However, this complex interplay is poorly considered in most studies (e.g., miR-21, [12]; let-7 [13], tristetraprolin [14]), and thus, our current comprehension of miRNA/RBPs biology in physiological and pathological processes is strongly limited, as evidenced by the increasing number of contradictory findings in the literature regarding microRNA's functions [15,16]. This can be explained by the difficulty of fully recapitulating this degree of complexity in current preclinical models. In this review, our goal is to describe part of this complex regulatory network in human cancers, with an emphasis on the interplay between the most studied AUBPs (TTP family members and HuR) and miRNAs-dependent regulation.

MiRNAs: From Biogenesis to a Complex Regulatory Network
MicroRNAs are small endogenous ≈20 nucleotides non-coding sequences promoting mRNA decay or translation inhibition through their ability to bind to a specific seed sequence in the 3 UTR of target mRNAs [17][18][19]. In the canonical model, the perfect complementarity between the mRNA and the seed sequence of miRNAs leads to mRNA decay, while imperfect complementarity is thought to mediate translation inhibition [19]. However, this model is not completely understood. MiRNA biogenesis starts with the generation of a primary miRNA transcript (pri-miRNA) by RNA polymerase II/III [19]. Then, the pri-miRNA is cleaved by the microprocessor complex comprised of the ribonuclease III enzyme, Drosha and the RBP DGCR8 (DiGeorge Syndrome Critical Region 8), thereby producing a precursor miRNA (pre-miRNA), which is exported to the cytosol via the Exportin5/RanGTP [19]. In the cytosol, pre-miRNAs are processed by the RNase III endonuclease Dicer, which removes the terminal loop, thereby producing a mature miRNA duplex comprised of a guide strand and a complementary passenger strand (miRNA*) [19]. Although it was originally thought that only the guide strand is important for targeted gene silencing, it is now clear that depending on the cell type or the context (e.g., inflammation, deregulated metabolism), both strands can associate with argonaute proteins and incorporates into the RNA-Induced Silencing Complex (RISC), where it binds to its target mRNAs [19]. MiRNAs can regulate hundreds of mRNAs, and conversely, one mRNA can be regulated by multiple miRNAs. Moreover, depending on the cellular or physiological context (e.g., nutrients deprivation, hypoxia, treatment with anti-tumor agents), miRNAs may exert different functions and regulate different targets. Finally, miRNAs are subjected to sequence editing during processing (e.g., A-to-I), which strongly alters their binding properties and the choice of the strand incorporated into the RISC [20,21]. Considering this complexity, the current models and approaches to study miRNA-dependent regulation appear quite simplistic. Another layer of complexity comes from other trans-acting factors that control the fate of mRNAs and interfere with miRNA-dependent regulation or are regulated by miRNAs. This includes lncRNAs but also RBPs, such as AUBPs, which can compete with the same binding sites with miRNAs, cooperate with miRNAs or act as "sponges" to sequester miRNAs, thereby preventing their binding to their target mRNA [22,23]. Whether a miRNA is active or not, therefore, depends on the availability of the seed sequence on target mRNA and the bioavailability of miRNAs in each system. However, for most studies, only miRNAs with the most deregulated expression are considered in the pathophysiology of human diseases. This choice is potentially wrong, given that the deregulated expression of mRNAs does not always translate into a deregulated activity [24,25]. Finally, the complexity of such a regulatory network is further enhanced by the ability of several miRNAs to control the expression of AUBPs. Deciphering this complex regulatory network is therefore crucial for identifying bioavailable and active miRNAs involved in physiological and pathological processes. Emerging databases (e.g., SIMIRA) can provide some help in predicting the common targets between RBPs and miRNAs (http://vsicb-simira.helmholtz-muenchen.de, accessed on 1 June 2022). Immunoprecipitation assays of RBPs coupled with RNAseq are also highly relevant for identifying all non-coding RNAs bound to RBPs [26][27][28]. These data are publicly available in specific databases (http://clipdb.ncrnalab.org, accessed on 1 June 2022; http://rbpdb.ccbr.utoronto.ca/, accessed on 1 June 2022). Finally, the complexity of this regulatory network should be better represented in the in vitro and in vivo models. Developing models that consider the interplay between miRNAs and these other trans-acting factors represents a relevant approach to fully characterize the role of these post-transcriptional regulators and uncover novel and efficient therapeutic approaches.

AUBPs Interfering with miRNAs-Dependent Regulation
AUBPs represent a family of RBPs controlling gene expression at the post-transcriptional level [9,29]. These proteins have a high affinity for Adenine and Uridine-rich elements (ARE: e.g., AUUUA pentamer) within the 3 UTR of several immediate-early response genes (which represent about 5-8% of the human transcriptome) and mediate their decay and/or impair their translation through processes involving their recruitment into small cytoplasmic compartments, namely, Stress Granules (SGs) or processing-bodies (P-bodies), respectively [9,29]. More than 20 different AUBPs have been identified and display varying expression patterns depending on the tissue type or the physiological context (e.g., inflammation, hypoxia, chemotherapy) [9]. While some AUBPs promote mRNA decay (e.g., tristetraprolin family members:), others are mostly stabilizing their target mRNAs (e.g., Human Antigen R, HuR) and/or blocking their translation (e.g., T-cell Intracellular Antigen-1, TIA1) [9,[29][30][31][32]. However, emerging studies showing opposite functions currently challenge this very strict and dogmatic view. The activity and subcellular localization of these proteins are regulated by various post-translational modifications (e.g., phosphorylation, methylation), depending on the cellular context (e.g., mitosis, endoplasmic reticulum, and oxidative stress) [33][34][35]. Alteration of AUBPs expression/activity contributes to deregulated expression patterns of genes involved in inflammatory (e.g., PTGS2, TNFA) [31,36,37], metabolic (e.g., FGF21, PTEN) [38,39] and carcinogenic processes (oncogenes/tumor suppressors, e.g., MYC, P53) [40,41] and thus contributes to the development of a wide range of chronic metabolic/inflammatory diseases and cancers [9,29]. Importantly, these proteins can also compete with each other for the same mRNA targets (e.g., HuR and TTP for COX-2) [30], and increasing evidence indicates that these proteins can regulate gene expression by interfering with miRNA-dependent regulation [42,43]. Herein, we discuss these complex interactions and their role in cancer development, with an emphasis on HuR and TTP family members. The different connections between HuR, TTP family members and miRNA-dependent regulation of gene expression are discussed below and are summarized in Figures 1 and 2. Antagonisms between HuR and microRNA-dependent regulation. HuR can interfere with miRNA-dependent regulation by different mechanisms: (i) HuR and miRNAs can compete for the binding to mRNAs due to overlapping binding sites; (ii) HuR, in concert with lncRNAs, can indirectly compete with miRNAs; (iii) HuR can directly sequester or inhibit miRNA expression; (iv) HuR can inhibit miRNA maturation (i.e., miR-199a); (v) HuR can promote lncRNA-dependent miRNA sponging. ONCO: Oncogenes; TS: Tumor Suppressor. Antagonisms between HuR and microRNA-dependent regulation. HuR can interfere with miRNA-dependent regulation by different mechanisms: (i) HuR and miRNAs can compete for the binding to mRNAs due to overlapping binding sites; (ii) HuR, in concert with lncRNAs, can indirectly compete with miRNAs; (iii) HuR can directly sequester or inhibit miRNA expression; (iv) HuR can inhibit miRNA maturation (i.e., miR-199a); (v) HuR can promote lncRNA-dependent miRNA sponging. ONCO: Oncogenes; TS: Tumor Suppressor.

Figure 2.
Cooperation between HuR, TTP and microRNA-dependent regulation. (A) HuR can cooperate with miRNAs by directly interacting with miRNAs and favoring their binding to their target mRNAs. This effect can also require the binding of circRNA (e.g., circ_CCNB1). HuR promotes exosome-dependent miR-1246 secretion. HuR can stabilize JUNB mRNAs, thereby favoring its overexpression, which in turn promotes miR-494 expression. (B) Finally, TTP can promote let-7 expression, which, in turn, decreases its mRNA targets (e.g., CDC34).

HuR
HuR (encoded by ELAVL1: Embryonic-Lethal Abnormal Vision in Drosophila) is ubiquitously expressed AUBPs, which possess two tandems RNA-Recognition motif (RRM), and a hinge region followed by a third RRM [44,45]. The hinge region is subjected to various post-translational modifications (e.g., phosphorylations, methylation) and is mostly involved in the nucleo-cytoplasmic shuttling of HuR [46,47]. In the cytosol, HuR exerts its mRNA stabilizing function by targeting ARE and competing or displacing other destabilizing factors (e.g., miRNAs, TTP family members) with overlapping binding sites [48]. Finally, HuR can also sequester or potentiate miRNA functions [42]. HuR expression is frequently upregulated in human cancers and plays a compelling role in carcinogenic processes [44,45]. HuR has mostly been associated with tumor-promoting functions due to its ability to stabilize a whole set of oncogenic and pro-inflammatory transcripts (e.g., COX-2) [49]. However, increasing evidence indicates that HuR can interfere with miRNA-dependent regulation [42] and can exert tumor suppressive functions. Understanding the Figure 2. Cooperation between HuR, TTP and microRNA-dependent regulation. (A) HuR can cooperate with miRNAs by directly interacting with miRNAs and favoring their binding to their target mRNAs. This effect can also require the binding of circRNA (e.g., circ_CCNB1). HuR promotes exosome-dependent miR-1246 secretion. HuR can stabilize JUNB mRNAs, thereby favoring its overexpression, which in turn promotes miR-494 expression. (B) Finally, TTP can promote let-7 expression, which, in turn, decreases its mRNA targets (e.g., CDC34).

HuR
HuR (encoded by ELAVL1: Embryonic-Lethal Abnormal Vision in Drosophila) is ubiquitously expressed AUBPs, which possess two tandems RNA-Recognition motif (RRM), and a hinge region followed by a third RRM [44,45]. The hinge region is subjected to various post-translational modifications (e.g., phosphorylations, methylation) and is mostly involved in the nucleo-cytoplasmic shuttling of HuR [46,47]. In the cytosol, HuR exerts its mRNA stabilizing function by targeting ARE and competing or displacing other destabilizing factors (e.g., miRNAs, TTP family members) with overlapping binding sites [48]. Finally, HuR can also sequester or potentiate miRNA functions [42]. HuR expression is frequently upregulated in human cancers and plays a compelling role in carcinogenic processes [44,45]. HuR has mostly been associated with tumor-promoting functions due to its ability to stabilize a whole set of oncogenic and pro-inflammatory transcripts (e.g., COX-2) [49]. However, increasing evidence indicates that HuR can interfere with miRNA-dependent regulation [42] and can exert tumor suppressive functions. Understanding the molecular traits associated with HuR's functions is, therefore, determinant prior to any therapeutic intervention, as suggested by HuR inhibitors (e.g., MS-444, DHTS, KH-3) in several cancers [50][51][52].

Competitive Antagonism between HuR and miRNAs
HuR-miR-21: MiR-21 is a well-known miRNA frequently upregulated in human cancers and associated with pro-tumorigenic functions and a poor clinical outcome in patients [53][54][55]. Increasing evidence indicates that HuR can prevent the miR-21-dependent function. Indeed, the RBP, lupus antigen (La), together with HuR, binds to the 3 UTR of PDCD4 (Programmed Cell Death Protein 4), a tumor suppressor, to prevent the binding of miR-21 [56]. Although HuR is mostly considered a tumor-promoting factor, these findings suggest a tumor suppressive role of HuR. The tumor-promoting properties of miR-21 have essentially been uncovered in vitro in transformed cancerous cell lines [53]. However, our previous study demonstrated for the first time that, in contrast to in vitro findings, miR-21 could also exert tumor suppressive properties [57]. Therefore, these data suggest a context-dependent function of HuR and miR-21. In agreement, the binding of HuR to PDCD4 mRNA is prevented in oxidative stress conditions (H 2 O 2 ) due to the phosphorylation of HuR by ERK8 (Extracellular Signal Regulated Kinase 8), as evidenced in Hela cells [58]. Taken together, these data suggest cautions regarding the dogmatic statement of miR-21 functions in cancer cells, based on the miRNA expression only, without considering its activity. A better characterization of this interplay is therefore required prior to the development of any therapeutic approaches aiming at targeting miR-21 or HuR in cancers.
HuR-OIP5-AS1 and miR-424. As described previously in colon cancer, HuR stabilizes the lncRNA OIP5-AS1 in human cervical cancer cells (Hela cell line). Moreover, OIP5-AS1 acts as a decoy to prevent the binding of HuR on mRNA targets, thereby reducing cancer cell proliferation. In contrast, miR-424 competes with HuR and downregulates OIP5-AS1 expression [61].
HuR-miR-16. In breast cancer cells, the regulation of cyclin E1 mRNA (CCNE1) depends on the interplay between HuR and miR-16 [62]. Indeed, in a luciferase-reporter construct, HuR blocks the binding of miR-16 on the 3 UTR of CCNE1 in MCF-7 cells. While this effect was not observed with the endogenous CCNE1 transcript, miR-16 was able to prevent the HuR-dependent CCNE1 stabilization. Together, these findings highlight the importance of this interplay during cell cycle progression.
HuR-miR-194/miR-206. Nucleolin (NCL) is overexpressed in several malignancies and promotes cancer cell proliferation [63]. This overexpression of NCL is mediated by the elevated expression of HuR and the downregulation of miR-194 and miR-206, which competitively bind to NCL 3 UTR, as evidenced in MCF-7 and MDA-231 cells (breast cancer cells) [64].
HuR-OSER1-AS1-miR-17-5p. OSER1-AS1 is a lncRNA with tumor suppressive properties in Non-Small Cell Lung Cancer (NSCLC). In agreement, the loss of its expression in tumor from patients correlates with a poor clinical outcome. In the H1299 cell line, OSER1-AS1 binds to HuR and acts as a decoy to prevent HuR from stabilizing its mRNA target. On the other hand, miR-17-5p competes with HuR to bind and downregulate OSER1-AS1 [65].
HuR-miR-548c-3p. Topoisomerase II alpha (TOP2A) is a key enzyme involved in cell proliferation, which is frequently overexpressed in cancers of different origins and influences the efficiency of the chemotherapeutic agent (e.g., doxorubicin) [66][67][68]. Recently, it has been suggested that the expression of TOP2A is regulated by HuR and miR-548c-3p, which competes for the binding to TOP2A 3 UTR [69]. Indeed, in Hela cells, HuR binds directly to mRNA (TOP2A) and increases its translation [69], while miR-548c-3p reduces TOP2A protein expression.
HuR-miR-133b. In gastric cancer (GC) tissue and cell lines (BGC-823, MKN-45, MGC-803, SGC-7901, and AGS), HuR expression is high and promotes cancer cell proliferation and migration in vitro and in vivo [72]. This effect is mediated by the ability of HuR to decrease miR-133b expression, which exerts a tumor suppressive function in GC cells. Furthermore, HuR stabilizes CDC5L (cell division cycle 5-like protein) mRNA, while miR-133b inhibits its expression. Therefore, the overexpression of CDC5L, which promotes cell cycle progression, results from the overexpression of HuR and the loss of miR-133b in GC cells [72].
HuR-miR-4319. Semaphorin 4D (SEMA4D) is overexpressed in esophageal squamous cell carcinoma (ESCC) cells and contributes to cancer progression [73]. A competition between HuR and miR-4319 for the binding to SEMA4D mRNA has been demonstrated in ESCC cells (KYSE-150, TE-10 and TE-1). While HuR stabilizes SEMA4D mRNA and contributes to cell proliferation and migration in ESCC, miR-4319 overexpression destabilizes SEMA4D mRNA and prevents ESCC progression [73]. Interestingly, the expression of miR-4319 is low in ESCC cells [74], while HuR is overexpressed [75], thus indicating that SEMA4D overexpression in ESCC is mediated by this double hit.
HuR-miR-300. In gastric cancer, the expression of UBE2C (Ubiquitin Conjugating Enzyme E2 C), a potent tumor promoter [76], is under the regulation of HuR, which stabilizes its mRNA by preventing the binding of miR-300 [77].
HuR-miR-675-5p. HuR importantly contributes to cancer cell survival and aggressiveness during hypoxia by stabilizing HIF1A (Hypoxia Inducible Factor 1 Subunit Alpha) mRNA, as evidenced in glioma cells (U51). In contrast, miR-675-5p competes with HuR for the binding to HIF1A expression and promotes its downregulation [83]. These findings highlight an important mechanism involved in glioma progression.
HuR-miR-320a. This interplay importantly regulates the DNA damage response by controlling the expression of NONO, a RBP involved in the S phase checkpoint of the cell cycle [84]. In Hela cells, ultra-violet (UV) irradiation increases miR-320 expression in a p53-dependent manner [84] but fails to downregulate NONO expression due to the induction of HuR, which stabilizes NONO mRNA by competing with miR-320a. Accordingly, HuR inhibition destabilizes NONO mRNA, and the concomitant silencing of miR-320a restores NONO expression. These findings suggest that HuR represent an important barrier against the DNA damage response in cancer cells, which may represent an appealing therapeutic target.
HuR-miR-124-3p. In ovarian cancer, HuR overexpression contributes to increased stability of NEAT1 (Nuclear Enriched Abundant Transcript 1), a lncRNA promoting cancer cell proliferation and invasion [85]. In contrast, NEAT1 expression is suppressed by miR-124-3p [85]. However, it is unclear in this study whether HuR and miR-124-3p compete for the same binding sites. Nevertheless, it is likely that the overexpression of NEAT1 in cancer cells is a consequence of both HuR overexpression and miR-124-3p silencing.
HuR-miR-125b. HuR binds to adjacent binding sites of miR-125b in the 3 UTR of P53 mRNA in MCF7 human breast carcinoma cells [86]. Upon ultraviolet C (UVC) exposure, HuR translocates from the nucleus to the cytosol, where it binds to P53 mRNA, thus preventing miR-125b-mediated translation inhibition of P53. This interplay is, therefore, important for the DNA damage response [86].
HuR-miR-200b. In bone marrow-derived macrophages (BMDMs) derived from myeloidspecific HuR KO mice, miR-200b expression is increased, and a computational analysis has revealed that miR-200b binding sites overlap with HuR binding sites on several transcripts [87]. Among them, HuR stabilizes VEGFA (Vascular Endothelial Growth Factor A) mRNA by preventing miR-200b binding. These findings demonstrate the importance of this competition in angiogenesis.
HuR-other miRNAs. A miRNA-binding site mapping in wild-type and HuR knockout macrophages indicate that HuR binding sites overlap with other miRNAs (i.e., miR-27) [90]. Moreover, a transcriptome-wide analysis has allowed identifying 788 HuR bound 3 UTR among the 2653 AGO2 bound 3 UTR [91]. Finally, other mechanisms have been described in chronic disorders fostering carcinogenesis, such as the competition between HuR and miR-30e for the regulation of sphingosine 1-phosphate receptor 3 (S1PR3) during liver fibrosis [92]. A potential interplay between HuR, miR-873 and miR-125a-3p has also been suggested for the regulation of cancer stemness through the regulation of CDK3 (Cyclin Dependent Kinase 3) expression in lung cancer [93]. However, the nature of this interplay was not fully depicted in this study. Finally, HuR may also affect the activity of other miRNAs through its ability to inhibit AGO2. Indeed, the circular RNA (circAGO2) generated from the AGO2 gene can bind to HuR protein and facilitate its translocation to the cytoplasm, thereby promoting its binding to the 3 UTR of several transcripts (i.e., EIF4EBP3, HNF4A, MAP4K1, NOTCH4, SLC2A4, and SLC44A4) and reducing AGO2/miRNA-dependent regulation (miR-224-5p, miR-143-3p, miR-181a-5p, miR-503-5p, or miR-125a-3p) [94]. CircAGO2 is overexpressed in various cancers, where it correlates with a poor prognosis and promotes tumorigenesis and aggressiveness [95]. Therefore, the circAGO2/HuR interplay represents a major oncogenic axis that should be considered in other malignancies.
HuR-miR-16. In colorectal cancer, cyclooxygenase 2 (COX-2), a major enzyme of inflammation, is frequently overexpressed and promotes various cancerous hallmarks [97]. This overexpression is due to the ability of HuR to directly bind and stabilize its mRNA transcript. In addition, HuR binds directly and sequesters miR-16, which directly inhibits COX-2, expression [98]. HuR-miR-107: In non-small cell lung cancer cells (NSCLC, A549, H1299, Calu6 and H520) ALKBH5 (AlkB homolog 5), inhibits Hippo/YAP signaling and reduces cancer cell proliferation, migration, and invasion [99]. This effect is partially promoted by an increased expression of HuR, which in turn prevents miR-107-dependent downregulation of LATS2 (Large Tumor Suppressor Kinase 2) [99,100]. In this study, HuR binds directly to miR-107 and acts as a miRNA sponge. These findings suggest a tumor suppressive function of HuR.
HuR-UFC1-miR-34a. UFC1 is a lincRNA overexpressed in HCC [101] and acts as a tumor promoter by favoring cancer cell proliferation, inhibiting apoptosis in vitro and in vivo. This effect is partially attributed to its ability to increase β-catenin expression by interacting with HuR. In contrast, miR-34a is a negative regulator of UFC1 and thus prevents the induction of β-catenin in cancer cells [101].
HuR-LINC00336-miR6852. LINC00336 is upregulated in lung cancer and promotes cancer-related processes by acting as a competing endogenous RNA (ceRNA) on miR-6852 [103]. This miRNA is an important regulator of cystathionine-β-synthase (CBS) expression, an inhibitor of ferroptosis [103]. HuR, which is overexpressed in lung cancer, binds to LINC00336 and stabilizes it, thus inhibiting miR-6852 and favoring CBS expression. Accordingly, miR-6852 overexpression reduces cancer cell proliferation (A549 cells) and survival by inducing ferroptosis.
HuR-circ-CCND1-miR-646. In laryngeal squamous carcinoma, circ-CCND1 importantly promotes cancer-related processes by sponging miR-646, which inhibits CCND1 (cyclin D1) expression [105]. In parallel, circ-CCND1 interacts with HuR to stabilize CCND1 mRNA [105]. However, these two mechanisms seem to act independently of each other, and thus the overexpression of CCND1 is more a consequence of a coordinated effect of HuR and miR-646 rather than an interplay between them.
HuR-miR-199a. HuR is an important regulator of miR-199a maturation [108] in hepatocellular carcinoma in hypoxic conditions. Hypoxia induces HuR expression and promotes its binding to the primary miR-199a (pri-miR-199a), thereby inhibiting its maturation. Due to the ability of miR-199a to regulate hexokinase-2 (HK2) and pyruvate kinase-M2 (PKM2), this interplay strongly contributes to the metabolic switch of HCC cells toward glycolysis during hypoxia [108].
HuR-HOTAIR and miR-7. In Neck Squamous Cell Carcinoma, the lncRNA Homeobox (HOX) transcript antisense RNA (HOTAIR) is overexpressed, and this effect is partially mediated by HuR, which directly binds and stabilizes HOTAIR [111]. HOTAIR acts as a miRNA sponge on miR-7 to promote cancer cell (CC25 and FaDu cells) proliferation, migration, and invasion.
HuR-H19 and miR-675. HuR interacts directly with the lncRNA H19 in the placenta and prevents its processing for the biogenesis of miR-675 [112]. This inhibitory effect occurs during the processing by drosha [112]. However, it is unclear whether this link exists in human cancers. Moreover, depending on the cancer type, miR-675 expression is reduced or overexpressed and displays both oncogenic (e.g., Non-Small Cell lung cancer, [113] and tumor-suppressive properties (e.g., prostate cancer, [114]). In contrast, H19 is upregulated and promotes cancer progression. Therefore, the induction of HuR, frequently observed in human cancer, may inhibit miR-675 expression in cancer cells. However, this link remains to be determined.

Cooperation between HuR and miRNAs
HuR-let-7. HuR can potentiate the effect of some miRNAs, as exemplified by let-7, which binds to the 3 UTR of c-Myc more efficiently when HuR binds to a proximal ARE site [115,116]. This interplay promotes a translational repression of c-Myc due to the ability of HuR to promote the interaction between AGO2/let-7b/c with c-Myc mRNA. Given the oncogenic potential of c-Myc [117], this study questions the dogmatic view of HuR as a strict oncogenic/tumor-promoting factor. Interestingly, both the expression of HuR and c-Myc are enhanced in most cancers, while the expression of let-7b and c is frequently decreased [118][119][120][121]. These findings suggest a decoupling between HuR and Let-7 in cancer cells, thereby preventing the ability of HuR to inhibit the translation of oncogenic transcripts (e.g., c-Myc). Re-expressing let-7 expression may, therefore, represent a potent therapeutic approach by restoring the capacity of HuR to inhibit the translation of several transcripts. The cooperation between HuR and let-7b/RISC, favoring tumor progression, has also been described in HeLa cells. HuR recruits let-7b and both binds to and downregulates lincRNA p21. LincRNA p21 directly binds and prevents the translation of β-catenin and JUNB [122]. Therefore, the HuR-let-7b axis favors β-catenin and JUNB protein expression in cancer cells.
HuR-miR-9. In Hodgkin lymphoma, miR-9 directly represses several cytokines, including IL-6 (interleukin-6), TNFα (tumor necrosis factor-alpha), and CCL-5 (C-C Motif Chemokine Ligand 5). Interestingly, the regulation of IL-5 (interleukin-5) and TNFα is HuR-dependent. Indeed, the knockdown of HuR in HEK293T cells increases the expression of these cytokines, and this effect is prevented by the inhibition of miR-9. Although the underlying mechanism has not been fully depicted, these data suggest that HuR and miR-9 cooperate for the regulation of these cytokines [123].
HuR-miR-19a and b. MiRNAs bind to their targets through a specific base pairing between their seed sequence and the target mRNAs [17][18][19]. However, increasing evidence indicates a non-canonical mechanism of miRNAs binding, which is mediated by HuR. More precisely, in breast cancer cells, ABCB1 (P-glycoprotein), a multidrug resistance protein, is regulated by miR-19b despite the absence of miR-19b binding sites within the 3 UTR of ABCB1 mRNA [124]. The binding of miR-19 is mediated by HuR [124], thus suggesting that this cooperation importantly controls the chemosensitivity of cancer cells. Interestingly, HuR is also important for miR-19-dependent regulation of Ras homolog B (RhoB) in keratinocytes upon UV exposure [125]. Finally, in papillary thyroid cancer cells (BCAP) and HEK-293T cells, HuR overexpression promotes miR-19a synthesis, while its silencing reduces miR-19a levels [126]. This effect is mediated by the binding of HuR to pre-miR-19a, thereby increasing its stability and favoring its maturation. These findings further indicate that HuR is not only an mRNA stabilizing factor. Interestingly, this study suggests that the HuR-miR-19a/b axis promotes cancer cell proliferation. However, miR-19a targets Ras-related RAP-IB (RAP1B), a GTPase member of the Ras-associated protein family (RAS), which is overexpressed in BCAP and promotes cancer cell proliferation, migration, and invasion [127]. Further investigations are, therefore, required to fully characterize the importance of the HuR/miR-19a axis in carcinogenesis.
HuR-miR-1246. In gastric cancer cells (AGS cells), HuR binds to an ARE present on miR-1246 and promotes its secretion in the exosome [128]. Although the underlying mechanism is still unclear, exsosomal miR-1246 is frequently observed in the serum of patients with GC and may contribute to various cancerous processes [129][130][131].
HuR-miR-200a. MiR-200a and HuR cooperate to stabilize c-Jun mRNA, as evidenced in HEK293T cells [132]. This study challenges again the dogmatic view of miRNAs as strict gene expression repressors and indicates that this mechanism can contribute to the overexpression of important oncogenes.
HuR-miR-200c. In ovarian cancer, the role of miR200c depends on the localization of HuR. Indeed, when HuR is in the nucleus, miR200c acts as a tumor suppressor by inhibiting the expression of TUBB3 (class III β-tubulin) mRNA. In contrast, when HuR localizes in the cytoplasm, miR200c binds to HuR and acts in concert to stabilize TUBB3 mRNA, thus promoting carcinogenesis [133]. Together, these data further indicate that HuR exerts a dual function depending on the context, which influences HuR localization.
HuR-circular RNAs. Increasing evidence indicates an interplay between HuR and lncRNAs, which is not limited to their ability to sponge miRNAs. The circZNF609 RNA interacts with HuR to stabilize CKAP5 (Cytoskeleton Associated Protein 5) mRNA [135], a cytoskeleton/mitosis-associated factor, in RD cells (embryonal rhabdomyosarcoma cell line). Similarly, HuR and AGAP2-AS interact and stabilize CPT1A (Carnitine Palmitoyltransferase 1A) in mesenchymal stem cells, thereby promoting trastuzumab resistance in breast cancer [136]. CCAT2 (Colon Cancer Associated Transcript 2), a lncRNA, interacts with HuR in the nucleus to promote HCC progression, potentially by regulating the expression of autophagy-related genes [137]. Finally, HuR interacts with circCCNB1 and miR-516b-5p and cooperates to stabilize cyclin-D1 (CCND1) mRNA in glioma, thereby favoring cancer progression [138].
HuR-RPSAP52-miR-15a, miR-15b, and miR-16. This interplay between HuR, the lncRNA RPSAP52 (Ribosomal Protein SA Pseudogene 52) and miRNA-dependent regulation has been associated with the regulation of the cell cycle inhibitor, p21, in colorectal cancer cells (HT-29) [139]. In this study, RPSAP52 directly binds to HuR protein, thereby preventing its ability to stabilize CDKN1A (Cyclin Dependent Kinase Inhibitor 1A) transcript. In addition, RPSAP52 shifts the localization of miR-15a, miR-15b and miR-16 from HMGA (High Mobility Group AT-Hook 1) to CDKN1A mRNA. One potential explanation discussed in this study is the change in mRNA conformation, thus allowing better access of miRNA to CDKNA1.
HuR-other miRNAs. Although HuR has mainly been associated with a stabilizing function, this dogmatic view is further challenged by other studies showing cooperation between HuR and miRNAs in other diseases. For instance, HuR and miR-26 act synergistically to regulate the expression of the negative regulator of G-protein signaling 4 (Rgs4) in neurons [140]. Whether this cooperation exists in human cancers remains to be determined, but these findings suggest that this destabilizing function of HuR is underestimated in cancers and may be tissue dependent.

TTP Family Members (TTP, TIS11, GOS24, NUP475)
TTP is one of the most studied AUBPs, which belongs to the family of Cys-Cys-Cys-His zinc finger proteins [141][142][143]. This family contains three members, TTP (tristetraprolin, ZFP36), BRF1 (Butyrate response factor 1, ZFP36L1) and BRF2 (Butyrate response factor 2, ZFP36L2) [143]. TTP is rapidly induced by various stimuli, including TGF-β (transforming growth factor-beta) [144,145], LPS (lipopolysaccharide) [146], TNFα, or insulin [147,148] and is, therefore, considered as an immediate-early response gene [9]. TTP is one of the bestcharacterized AUBPs involved in ARE-mediated mRNA decay through a process involving the nucleation of small cytoplasmic granules called (P-bodies), where the target mRNAs are bound by various enzymes promoting deadenylation, decapping and degradation [9,149]. The importance of TTP in physiological/pathological processes is illustrated by Zfp36 knockout mice, which develop a severe inflammatory syndrome and growth retardation due to the overexpression of pro-inflammatory factors (e.g., TNF-α) [9,150,151]. TTP is mostly considered a tumor suppressor whose expression is lost in tumors. This effect is due to its ability to control a whole network of oncogenic and pro-inflammatory transcripts [9]. However, this concept has recently been challenged in HCC, where TTP plays a potent pro-tumorigenic function in vivo, as evidenced in liver specific TTP KO mice treated with a hepatic carcinogen (i.e., diethylnitrosamine) [152]. The interplay between TTP and miRNAdependent regulation is poorly known and even less understood in the context of cancer. TTP can cooperate with some miRNAs, such as miR-16, as evidenced in drosophila S2 cells [153]. MiR-16 sequence (UAAAUAUU) is complementary to the canonical ARE sequence. This cooperation requires the binding of TTP to AGO/EIF2C family members to assist miR-16 binding to ARE on its target [153] mRNAs. Moreover, TTP can also promote the expression of some miRNAs, as evidenced by let-7, whose expression is increased by ectopic overexpression of TTP in various cancer cells (PA1, HCT-116) [154]. This effect leads to the downregulation of let-7 target genes, such as CDC34 (Cell Division Cycle 34), and reduces cancer cell proliferation [154]. Interestingly, this effect seems to be P53-dependent, as DNA-damaging agents such as doxorubicin trigger P53 activation and induce both TTP and let-7 expression [155]. These data also indicate that the expression of TTP is tightly dependent on the mutational landscape in cancer cells. However, it is currently unclear whether the expression of TTP is similarly affected by other mutations. Whether a specific mutation is associated with a specific post-transcriptional signature remains to be determined. Both TTP and let-7 are frequently downregulated in human cancers. Restoring TTP expression may, therefore, represent a potential approach to restoring let-7 expression in cancer cells. Several approaches aiming at restoring TTP expression in cancer cells have been proposed, such as DNA demethylating agents in hepatocellular carcinoma or histone deacetylase inhibitors (HDAC) in colorectal cancer and HCC [152,156]. In ovarian cancer cells (CaOV-3, SKOV-3, HEYA-8 cell lines), p70S6K (70 S6 kinase) phosphorylates and inhibits the interaction of TTP with Dicer, thereby reducing the expression of miR-145 [157]. Other studies have also demonstrated that TTP can reduce the expression of miRNAs, such as miR-155 in cystic fibrosis [158]. This effect is mediated by the induction of miR-1, which reduces miR-155 biogenesis in lung epithelial cells. Collectively, these findings indicate that TTP can indirectly control the expression of a myriad of transcripts by controlling the expression of miRNAs. This interplay is currently poorly known for the other TTP family members, BRF1 and BRF2. In lung cancer, the lncRNA MNX1-AS1 promotes cancer progression by interacting with miR-527, thereby preventing miR-527induced BRF2 downregulation. In this study, BRF2 importantly promotes cancer cell proliferation, migration, and invasion [159].

MiRNAs-Regulating HuR and TTP Family Members
Several miRNAs targeting AUBPs have been documented in different cancers. Targeting these miRNAs may, therefore, represent a potential therapeutic approach aiming at restoring the "beneficial" AUBPs. In this section, we discuss the miRNAs regulating the expression of the most studied AUBPs, TTP family members and HuR (Table 1 and Figure 3).

HuR
Several miRNAs regulating HuR expression have been identified in human cancers. Although HuR expression is increased in most neoplasms [160], this knowledge is limited to certain types of cancers and has essentially been demonstrated in vitro using cancer cell lines.
Gastric Cancer (GC): HuR expression is increased in GC as compared to normal tissue and contributes to tumor growth and metastasis [161]. This induction of HuR can be attributed to the loss of expression/activity of several miRNAs, including miR-145 [161], miR-519 [162] or miR-582-3p [163]. Interestingly, the activity of miR-582-3p is inhibited by a circular RNA, circSHKBP1, which is upregulated in GC. These data illustrate well the complex regulatory network regulating HuR expression, with various miRNAs and ncRNA acting in concert to increase HuR expression. Finally, not only the expression but also the cytoplasmic localization of HuR is under miRNAs influence in GC. Indeed, GAS5 (Growth Arrest Specific 5) directly binds to HuR and promotes its cytoplasmic translocation, thereby stabilizing the FAM83B (Family With Sequence Similarity 83 Member B) transcript and promoting cancer cell proliferation, migration, and invasion. MiR-140-3p, which is downregulated in GC patients, directly binds and inhibits the expression of GAS5, and thus, promotes HuR nuclear localization and the downregulation of FAM83B expression [164].
Hepatocellular Carcinoma (HCC). MiR-16 is a potent regulator of cyclooxygenase-2 expression in human hepatoma/HCC cells (Hep3B, WRL68) [165]. This effect is mediated by two different mechanisms with (i) a direct regulation of COX-2 mRNA by miR-16 and (ii) the ability of miR-16 to downregulate HuR expression, which stabilizes COX-2 mRNA. MiR-16 exerts tumor suppressive properties in vitro and in vivo (xenograft model), and its expression inversely correlates with COX-2 level in HCC tissue [165].

HuR
Several miRNAs regulating HuR expression have been identified in human cancers. Although HuR expression is increased in most neoplasms [160], this knowledge is limited to certain types of cancers and has essentially been demonstrated in vitro using cancer cell lines.
Gastric Cancer (GC): HuR expression is increased in GC as compared to normal tissue and contributes to tumor growth and metastasis [161]. This induction of HuR can be attributed to the loss of expression/activity of several miRNAs, including miR-145 [161], miR-519 [162] or miR-582-3p [163]. Interestingly, the activity of miR-582-3p is inhibited by a circular RNA, circSHKBP1, which is upregulated in GC. These data illustrate well the complex regulatory network regulating HuR expression, with various miRNAs and ncRNA acting in concert to increase HuR expression. Finally, not only the expression but also the cytoplasmic localization of HuR is under miRNAs influence in GC. Indeed, GAS5 (Growth Arrest Specific 5) directly binds to HuR and promotes its cytoplasmic translocation, thereby stabilizing the FAM83B (Family With Sequence Similarity 83 Member B) transcript and promoting cancer cell proliferation, migration, and invasion. MiR-140-3p, which is downregulated in GC patients, directly binds and inhibits the expression of Ovarian cancer. The upregulation of HuR in ovarian cancer is also associated with the downregulation of miRNAs, such as miR-139-3p, whose loss promotes tumor growth and metastasis of ovarian cancer cells [166]. Moreover, similarly to GC, miR-519 is also downregulated in ovary, lung, and kidney cancer, and miR-519 overexpression reduces tumor growth by reducing HuR expression [167,168].
Papillary thyroid carcinoma. In this cancer, only miR-31 downregulation has been associated with HuR overexpression [169]. In thyroid carcinoma, HuR is an important tumor promoting factor due to its ability to stabilize oncogenic transcripts [170], and thus, a better understanding of the post-transcriptional regulation of HuR is required to envisage novel therapeutic options.
Cervical cancer. Similarl to CRC, miR-324-5P and miR-519 are potent regulators of HuR expression in cervical cancer, which are downregulated in tumors and associated with radiotherapy resistance to cancer cells [168,180,181].
Rhabdomyosarcoma (RMS). In RMS cells (Rh30 cells), miR-29 interacts directly with HuR and acts as a decoy to prevent HuR binding to A20 mRNA (TNF Alpha Induced Protein 3), an upstream repressor of NFkB (Nuclear factor kappa B) [182]. In these cells, HuR overexpression leads to A20 downregulation. In RMS and osteosarcoma cells, as well as in tumor samples from patients (e.g., liposarcoma, RMS, osteosarcoma), the expression of A20 and miR-29 is low, while HuR is strongly upregulated. The decoy activity of miR-29 may reside in the precursor sequence of the miR, which contains putative binding sites for HuR. Together, these results provide further evidence that HuR can also function as an RNA-destabilizing factor.
Glioblastoma multiforme: miR-3127-5P is a direct regulator of HuR in glioma [183]. Interestingly, this miRNA is sponged by LncRNA gastric cancer-associated transcript 3 (GACAT3), which is upregulated in glioma tissues from patients and thus promotes HuR overexpression [183]. In glioma stem cells (GSCs), [184], miR-146b-5p is also a direct regulator of HuR, and its downregulation in glioma promotes HuR expression, which, in turn, negatively regulates the expression of LincRNA-p21, a long intergenic non-coding RNA involved in the inhibition of β-catenin expression and nuclear translocation in GSC [184].
Prostate cancer. MiR-133b is a potent regulator of HuR, which is downregulated in prostate cancer cells (PC3, DU-145 cell lines) [189]. Accordingly, overexpression of miR-133b decreases HuR expression through a direct binding to HuR 3 UTR. This negative impact on HuR expression induced docetaxel cytotoxicity in prostate cancer cells [190] by reducing the expression of ABCG2 (ATP Binding Cassette Subfamily G Member 2), a transporter involved in chemoresistance. HuR expression is also negatively regulated by miR-34a in paclitaxel-resistant PC3 cells (PC3PR). The downregulation of HuR by miR-34a leads to a decrease in SIRT1 (Silent mating type information regulation 2 homolog 1) and Bcl-2, thereby sensitizing cancer cells to paclitaxel [191].
Laryngeal squamous cell carcinoma. MiR-519a is a potent tumor suppressor in laryngeal squamous cells [194]. This effect is partially mediated by its ability to directly inhibit HuR expression, as evidenced in laryngeal squamous cell carcinoma human epithelial type 2 cells [194]. Interestingly, HuR is also directly regulated by miR-519b-3p in larynx squamous Hep-2 cells, and the expression of this miRNA is reduced in tumors from patients [195].
Hematologic malignancies. MiR-519 regulates HuR expression in HL60 cells (acute myeloid leukemia, AML) [196]. Overexpression of miR-519 in AML cells reduces cancer cell proliferation by reducing HuR expression, thus indicating that HuR is not only a pro-tumorigenic factor. Other miRNAs have been involved in HuR regulation in AML, including miR-199a-3p [197] and miR-25. However, this latest is an indirect regulator involving the regulation of the NOX4 (NADPH Oxidase 4)/JNK (JUN N-Terminal Kinase) axis involved in HuR phosphorylation and cytoplasmic translocation [198]. In multiple myeloma cells, miR-16 downregulation correlates with the overexpression of HuR [199]. These results have been demonstrated by using a statistical approach (LIMMA method). In T-Large Granular Lymphocyte Leukemia (T-LGLL), miR-146b is a regulator of HuR expression, which is downregulated in a STAT3 (Signal Transducer and Activator of Transcription 3)-dependent manner [200]. Finally, in a model of Hodgkin lymphoma (L428, L540 and KM-H2 cell lines), miR-9 directly targets HuR and inhibits its expression [123]. Accordingly, the use of miR-9 antagomiR promotes HuR upregulation [123]. In B lymphoma cells (RAMOS, Daudi), miR-17-19b binds and reduces MYC expression [201]. This effect is indirectly mediated by the downregulation of checkpoint 2 expression (CHK2), an upstream regulator of HuR phosphorylation. The decreased HuR phosphorylation promotes HuR binding to MYC, which reduces its translation [201].
Other potential miRNAs regulating HuR? The number of miRNAs regulating HuR expression is probably underestimated given that several miRNAs have been predicted in several databases (e.g., miRwalk: http://mirwalk.umm.uni-heidelberg.de/: accessed on 13 June 2022) but have not been validated yet ( Figure 3B,D). Therefore, it is likely that the overexpression of HuR in cancers may also result from a concerted effect of all these miRNAs.

Tristetraprolin (ZFP36)
TTP is mostly associated with tumor suppressive properties in human cancers, and accordingly, its expression is frequently reduced in tumors [143]. Although various mechanisms have been described (e.g., promoter methylation, constitutive protein degradation, HDAC-dependent silencing of transcription factors) [156,202], several miRNAs have been involved in its loss. Among them, miR-29a is a direct regulator of TTP, which is upregulated in breast cancer [188,203]. MiR-29a is also upregulated in pancreatic cancer [204] and promotes cancer cell proliferation and migration by directly targeting TTP, thereby increasing the expression of epithelial-mesenchymal transition (EMT) and inflammatory markers. Whether this link between miR-29a and TTP exists in other cancers remains unclear, but the expression of this miRNA is frequently increased in human cancers [205], while TTP expression is lost. MiR-182 is another well-known miRNA able to downregulate the expression of TTP in cancers, which is frequently overexpressed in tumors [206]. Interestingly, this miR-182/ZFP36 axis is also regulated by the circular RNA_00054 (circRNA_00054), which acts as a miRNA sponge against miR-182 [206]. Accordingly, overexpression of circRNA_00054 in breast cancer cells reduces miR-182 bioavailability, restores TTP expression and promotes cancer cell growth, invasion, and migration in vitro and in vivo. MiR-128a, which is upregulated in Acute Myeloid Leukemia (AML), is also a potential regulator of TTP expression, as demonstrated in AML cells (OCI-AML3 and APL/AML cells), where its knockdown strongly triggers TTP expression [207]. However, it is unclear in this study whether this effect is direct or not. In hepatocellular carcinoma, miR-9-5p is a direct inhibitor of TTP expression [208]. Interestingly, the transfer of exosomal SENP3-EIF4A1 inhibits tumor growth in vivo by sequestering miR-9-5p, thereby increasing TTP expression [208]. Finally, miR-200c was also identified as a direct regulator of TTP expression in mouse breast cancer cells (4TO7) [209].
Together, these findings strongly suggest that TTP loss is promoted by the concerted impact of several miRNAs on TTP mRNA. Like for HuR, the number of miRNAs regulating TTP expression is probably underestimated given that many other miRNAs are predicted to target ZFP36 mRNA but have not been validated yet ( Figure 3B, D).

Butyrate Response Factor 1 (ZFP36L1)
In contrast to HuR and TTP, very few miRNAs involved in ZFP36L1 regulation have been identified. Among them, miR-93-3P is strongly increased during wound healing in mice and contributes to keratinocyte proliferation by targeting ZFP36L1 mRNA. [210]. In glioblastoma multiforme (GBM) cells, overexpression of miR-129-5p reduces ZFP36L1 expression and impairs cancer cell proliferation, migration, and invasion [211]. High expression of ZFP36L1 in GBM patients correlates with a poor clinical outcome and correlates with the downregulation of miR-129-5p. Finally, miR-181b was suggested as a potential regulator of ZFP36L1 in Chronic Lymphocytic Leukemia (CLL). However, no validation experiments were provided in this study, and thus, the link between this miRNA and BRF1 remains to be firmly demonstrated [212].

Conclusions
In this review, we discussed several mechanisms associated with HuR and TTP family members, which indicate that these proteins form a complex regulatory network with non-coding RNAs, that can exert both oncogenic and tumor-suppressive functions. This level of complexity between these post-transcriptional regulators is poorly considered in human diseases but also in physiological processes (e.g., development), and thus, our current interpretation of their role in cancers is mostly incomplete and probably misleading. Moreover, emerging evidence indicates that these crosstalks also occur in preneoplastic stages, including chronic inflammatory and metabolic disorders, and thus may contribute to the onset of cancers [224,225]. These findings challenge the dogmatic function of some AUBP (e.g., HuR) and miRNAs (e.g., miR-21) in cancers and clearly indicate that miRNA activity is not reflected by their deregulated expression only but also their bioavailability. Taken together, these findings suggest cautions regarding the therapeutic approaches aimed at targeting miRNAs or AUBPs (e.g., HuR-specific inhibitors suggested for the treatment of cancers) [51,226]. Therefore, a better understanding of this regulatory network and of the impact of these therapeutic approaches on miRNA-dependent regulation of gene expression is needed prior to any clinical application. In this regard, one of the major issues is the current models available to study human diseases, which do not fully recapitulate the complexity of these interactions occurring in patients. Therefore, intense efforts are required to integrate these networks in more physiological models (in vivo) rather than assessing the role of individual regulators in vitro. In this review, we discussed the crosstalks between the AUBPs, HuR, TTP family members, and miRNAs, but it is likely that a higher level of complexity is occurring with other RBPs, lncRNA, ceRNA, and RNA editing. Although modeling this entire network is currently challenging, new bioinformatics tools (database repository, deep learning, artificial intelligence) [227] will represent an asset in the future to achieve this goal and to identify new players of carcinogenesis, which may represent novel therapeutic targets. Finally, identifying the miRNAs/lncRNA regulating AUBPs and thus important oncogenes and tumor suppressors is also of major importance for designing novel therapeutic approaches. The current findings indicate that this regulation depends on several miRNAs regulating HuR and TTP family members in concert. Targeting the most consistent mechanisms (e.g., miR-519 for HuR) may also represent an appealing approach for different cancers.